Tracking is the measurement by one or a group of sensors of the position and, often also, the orientation, of a person or object in a given space.
Tracking is an important aspect of, for example, the general field of Augmented Reality (“AR”) in which computer generated data and/or imagery is combined with a real world view of a given scene. An AR application might, for example, simulate a training session for firefighters wherein a firefighter trainee might “spray” extinguishing agent toward “fire particles.” The trainee may wear a helmet along with a head-mounted display through which the trainee can view the real world scene. A computer, in communication with the head-mounted display, generates images (including the “spray” and “fire particles”) that are superimposed on the real world scene and that are in proper registration with the real world scene regardless of how the firefighter trainee moves his head. Thus, for example, when the firefighter trainee looks down towards the ground, the computer may generate appropriate images of flames that are then superimposed on the real world scene or view, and when the firefighter looks up, the computer may generate images of billowing smoke and superimpose the same on the real world scene or view. In this way, a complete training session may be implemented without ever having to burn any structures, consume flammable substances, or unnecessarily place personnel (especially untrained personnel) in danger.
Those skilled in the art appreciate that to provide to the user the appropriate imagery at the appropriate time and to make a firefighting training exercise like that described above useful, it is necessary to closely and continuously track the position and orientation of the user's head (sometimes referred to as “pose”), and thus line of sight, to generate and display the appropriate images to the user. Consequently, precise tracking is of critical importance in the implementation of augmented reality systems. Indeed, if the tracking technology used for a given application cannot generate sufficiently precise tracking information or data, then the resulting computer generated imagery might actually be more of a hindrance or distraction than a help to the user in that such imagery may be improperly registered with the real world view or scene.
Precise tracking becomes even more important as the granularity of what a user expects to see increases. For example, AR is sometimes employed for other forms of training exercises in which, for example, outlines of selected parts of an intricate mechanical device (e.g., an engine) within the view of the user are superimposed on the real world view of the device. Thus, even the slightest change in the orientation of the user's head will substantially change the view and, as a consequence, the computer generated imagery to be combined with the real world view. There is, accordingly, a need to provide improved tracking systems and methodologies generally, and which may also have particular utility in the context of augmented reality systems.